The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Co-evolutionary algorithms are a class of adaptive search meta-heuristics inspired from the mechanism of reciprocal benefits between species in nature. The present work proposes a cooperative co-evolutionary algorithm to improve the performance of a radial basis function neural network (RBFNN) when it is applied to recognition of handwritten Arabic digits. This work is in fact a combination of ten...
It is fundamental work to translate the historical characters called "kuzushi-ji" into the contemporary characters in Japanese historical studies. In this paper, we develop the Japanese historical character recognition system using the directional element features and modular neural networks. Modular neural networks consist of two kinds of classifiers: a rough classifier to find the several...
In order to eliminate the shortcomings of traditional neural networks in handwritten Chinese characters recognition, such as the premature convergence, a novel intelligent method is presented, which uses the particle swarm optimization (PSO) algorithm with adaptive inertia weight to train the neural networks. The main idea is that the optimum weights and thresholds of the neural networks is acquired...
An evolutionary approach has been proposed to improve simplified fuzzy ARTMAP neural network performance for off-line font-based recognition of printed Persian alphabetical characters. Some of Persian characters are so similar to each other. We have defined and used some fuzzy sets in feature extraction to improve recognition of these characters. Also, the presentation order of training patterns to...
This paper proposes a model of human recognition that simulates a human's continuous change in observation from rough overall check to fine detailed check. It has been applied to banknote recognition. Banknote classification for twenty eight samples has demonstrated that the proposed method enables to identify not only the kind of a banknote but also its degree of weariness.
Expanding on an earlier study to objectively validate the hypothesis that handwriting is individualistic, we extend the study to include handwriting in the Arabic script. Handwriting samples from twelve native speakers of Arabic were obtained. Analyzing differences in handwriting was done by using computer algorithms for extracting features from scanned images of handwriting. Attributes characteristic...
The incremental learning system for a feature extraction unit in the character recognition system is described and experimental results are shown. The relationship between this learning system and neural networks (NN) are explained and the specifications of this method are described as an NN application. The improved version of this system which is related to the Gabor filter was tested and an accuracy...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.